Abstract

A small spectral imaging system is presented that images static or moving objects simultaneously as a function of wavelength. The main physical principle is outlined and demonstrated. The instrument is capable of resolving both spectral and spatial information from targets throughout the entire visible region. The spectral domain has a bandpass of 12 Å. One can achieve the spatial domain by rotating the system’s front mirror with a high-resolution stepper motor. The spatial resolution range from millimeters to several meters depends mainly on the front optics used and whether the target is fixed (static) or movable relative to the instrument. Different applications and examples are explored, including outdoor landscapes, industrial fish-related targets, and ground-level objects observed in the more traditional way from an airborne carrier (remote sensing). Through the examples, we found that the instrument correctly classifies whether a shrimp is peeled and whether it can disclose the spectral and spatial microcharacteristics of targets such as a fish nematode (parasite). In the macroregime, we were able to distinguish a marine vessel from the surrounding sea and sky. A study of the directional spectral albedo from clouds, mountains, snow cover, and vegetation has also been included. With the airborne experiment, the imager successfully classified snow cover, leads, and new and rafted ice, as seen from 10.000 ft (3.048 m).

© 2000 Optical Society of America

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References

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  1. G. Vane, ed., Imaging Spectroscopy II, Proc. SPIE834, (1988).
  2. W. L. Wolfe, Introduction to Imaging Spectrometers, Vol. TT25 of SPIE Tutorial Text Series (SPIE Press, Bellingham, Wash., 1997), pp. 1–147.
  3. E. Herrala, J. Okkonen, “Imaging spectrograph and camera solutions for industrial applications,” Int. J. Pattern Recogn. Artif. Intell. 10, 43–54 (1996).
    [CrossRef]
  4. T. S. Hyvarinen, E. Herrala, A. Dall’Ava, “Direct sight imaging spectrograph: a unique add-in component brings spectral imaging to industrial applications, in Digital Solid State Cameras: Designs and Applications, G. M. Williams, ed., Proc. SPIE3302, 165–175 (1998).
    [CrossRef]
  5. F. Sigernes, K. Heia, H. Nilsen, T. Svenøe, “Imaging spectroscopy applied in the fish industry?,” Norw. Soc. Image Process. Pattern Recogn. 2, 16–24 (1998).
  6. W. Niblack, Introduction to Digital Image Processing, 2nd ed. (Prentice-Hall, Englewood Cliffs, N.J., 1986), pp. 168–181.
  7. J. R. Arthur, L. Margolis, D. J. Withaker, T. E. McDonald, “A quantitative study of economically important parasites of walleye pollock (Theragra chalcogramma) from British Columbian waters and effects of postmortem handling on their abundance in the musculature,” Can. J. Fish Aquat. Sci. 39, 710–726 (1983).
    [CrossRef]
  8. T. C. Cheng, “Human parasites transmissible for seafood and related problems,” in Microbial Safety of Fishery products, C. O. Chichester, H. D. Graham, eds. (Academic, London, 1973), pp. 163–189.
    [CrossRef]
  9. M. B. Chitwood, “Nematodes of medical significance found in market fish,” Am. J. Trop. Med. Hyg. 19, 599–602 (1970).
    [PubMed]

1998

F. Sigernes, K. Heia, H. Nilsen, T. Svenøe, “Imaging spectroscopy applied in the fish industry?,” Norw. Soc. Image Process. Pattern Recogn. 2, 16–24 (1998).

1996

E. Herrala, J. Okkonen, “Imaging spectrograph and camera solutions for industrial applications,” Int. J. Pattern Recogn. Artif. Intell. 10, 43–54 (1996).
[CrossRef]

1983

J. R. Arthur, L. Margolis, D. J. Withaker, T. E. McDonald, “A quantitative study of economically important parasites of walleye pollock (Theragra chalcogramma) from British Columbian waters and effects of postmortem handling on their abundance in the musculature,” Can. J. Fish Aquat. Sci. 39, 710–726 (1983).
[CrossRef]

1970

M. B. Chitwood, “Nematodes of medical significance found in market fish,” Am. J. Trop. Med. Hyg. 19, 599–602 (1970).
[PubMed]

Arthur, J. R.

J. R. Arthur, L. Margolis, D. J. Withaker, T. E. McDonald, “A quantitative study of economically important parasites of walleye pollock (Theragra chalcogramma) from British Columbian waters and effects of postmortem handling on their abundance in the musculature,” Can. J. Fish Aquat. Sci. 39, 710–726 (1983).
[CrossRef]

Cheng, T. C.

T. C. Cheng, “Human parasites transmissible for seafood and related problems,” in Microbial Safety of Fishery products, C. O. Chichester, H. D. Graham, eds. (Academic, London, 1973), pp. 163–189.
[CrossRef]

Chitwood, M. B.

M. B. Chitwood, “Nematodes of medical significance found in market fish,” Am. J. Trop. Med. Hyg. 19, 599–602 (1970).
[PubMed]

Dall’Ava, A.

T. S. Hyvarinen, E. Herrala, A. Dall’Ava, “Direct sight imaging spectrograph: a unique add-in component brings spectral imaging to industrial applications, in Digital Solid State Cameras: Designs and Applications, G. M. Williams, ed., Proc. SPIE3302, 165–175 (1998).
[CrossRef]

Heia, K.

F. Sigernes, K. Heia, H. Nilsen, T. Svenøe, “Imaging spectroscopy applied in the fish industry?,” Norw. Soc. Image Process. Pattern Recogn. 2, 16–24 (1998).

Herrala, E.

E. Herrala, J. Okkonen, “Imaging spectrograph and camera solutions for industrial applications,” Int. J. Pattern Recogn. Artif. Intell. 10, 43–54 (1996).
[CrossRef]

T. S. Hyvarinen, E. Herrala, A. Dall’Ava, “Direct sight imaging spectrograph: a unique add-in component brings spectral imaging to industrial applications, in Digital Solid State Cameras: Designs and Applications, G. M. Williams, ed., Proc. SPIE3302, 165–175 (1998).
[CrossRef]

Hyvarinen, T. S.

T. S. Hyvarinen, E. Herrala, A. Dall’Ava, “Direct sight imaging spectrograph: a unique add-in component brings spectral imaging to industrial applications, in Digital Solid State Cameras: Designs and Applications, G. M. Williams, ed., Proc. SPIE3302, 165–175 (1998).
[CrossRef]

Margolis, L.

J. R. Arthur, L. Margolis, D. J. Withaker, T. E. McDonald, “A quantitative study of economically important parasites of walleye pollock (Theragra chalcogramma) from British Columbian waters and effects of postmortem handling on their abundance in the musculature,” Can. J. Fish Aquat. Sci. 39, 710–726 (1983).
[CrossRef]

McDonald, T. E.

J. R. Arthur, L. Margolis, D. J. Withaker, T. E. McDonald, “A quantitative study of economically important parasites of walleye pollock (Theragra chalcogramma) from British Columbian waters and effects of postmortem handling on their abundance in the musculature,” Can. J. Fish Aquat. Sci. 39, 710–726 (1983).
[CrossRef]

Niblack, W.

W. Niblack, Introduction to Digital Image Processing, 2nd ed. (Prentice-Hall, Englewood Cliffs, N.J., 1986), pp. 168–181.

Nilsen, H.

F. Sigernes, K. Heia, H. Nilsen, T. Svenøe, “Imaging spectroscopy applied in the fish industry?,” Norw. Soc. Image Process. Pattern Recogn. 2, 16–24 (1998).

Okkonen, J.

E. Herrala, J. Okkonen, “Imaging spectrograph and camera solutions for industrial applications,” Int. J. Pattern Recogn. Artif. Intell. 10, 43–54 (1996).
[CrossRef]

Sigernes, F.

F. Sigernes, K. Heia, H. Nilsen, T. Svenøe, “Imaging spectroscopy applied in the fish industry?,” Norw. Soc. Image Process. Pattern Recogn. 2, 16–24 (1998).

Svenøe, T.

F. Sigernes, K. Heia, H. Nilsen, T. Svenøe, “Imaging spectroscopy applied in the fish industry?,” Norw. Soc. Image Process. Pattern Recogn. 2, 16–24 (1998).

Withaker, D. J.

J. R. Arthur, L. Margolis, D. J. Withaker, T. E. McDonald, “A quantitative study of economically important parasites of walleye pollock (Theragra chalcogramma) from British Columbian waters and effects of postmortem handling on their abundance in the musculature,” Can. J. Fish Aquat. Sci. 39, 710–726 (1983).
[CrossRef]

Wolfe, W. L.

W. L. Wolfe, Introduction to Imaging Spectrometers, Vol. TT25 of SPIE Tutorial Text Series (SPIE Press, Bellingham, Wash., 1997), pp. 1–147.

Am. J. Trop. Med. Hyg.

M. B. Chitwood, “Nematodes of medical significance found in market fish,” Am. J. Trop. Med. Hyg. 19, 599–602 (1970).
[PubMed]

Can. J. Fish Aquat. Sci.

J. R. Arthur, L. Margolis, D. J. Withaker, T. E. McDonald, “A quantitative study of economically important parasites of walleye pollock (Theragra chalcogramma) from British Columbian waters and effects of postmortem handling on their abundance in the musculature,” Can. J. Fish Aquat. Sci. 39, 710–726 (1983).
[CrossRef]

Int. J. Pattern Recogn. Artif. Intell.

E. Herrala, J. Okkonen, “Imaging spectrograph and camera solutions for industrial applications,” Int. J. Pattern Recogn. Artif. Intell. 10, 43–54 (1996).
[CrossRef]

Norw. Soc. Image Process. Pattern Recogn.

F. Sigernes, K. Heia, H. Nilsen, T. Svenøe, “Imaging spectroscopy applied in the fish industry?,” Norw. Soc. Image Process. Pattern Recogn. 2, 16–24 (1998).

Other

W. Niblack, Introduction to Digital Image Processing, 2nd ed. (Prentice-Hall, Englewood Cliffs, N.J., 1986), pp. 168–181.

T. C. Cheng, “Human parasites transmissible for seafood and related problems,” in Microbial Safety of Fishery products, C. O. Chichester, H. D. Graham, eds. (Academic, London, 1973), pp. 163–189.
[CrossRef]

T. S. Hyvarinen, E. Herrala, A. Dall’Ava, “Direct sight imaging spectrograph: a unique add-in component brings spectral imaging to industrial applications, in Digital Solid State Cameras: Designs and Applications, G. M. Williams, ed., Proc. SPIE3302, 165–175 (1998).
[CrossRef]

G. Vane, ed., Imaging Spectroscopy II, Proc. SPIE834, (1988).

W. L. Wolfe, Introduction to Imaging Spectrometers, Vol. TT25 of SPIE Tutorial Text Series (SPIE Press, Bellingham, Wash., 1997), pp. 1–147.

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Figures (9)

Fig. 1
Fig. 1

Three-dimensional optical diagram illustrating the main characteristics of our multipurpose spectral imager: L1, front lens; S1, entrance slit; L2, collector lens; G, grating; P, prism; L3, camera lens; and CCD, imaging detector. The optical axis is parallel to the X axis of the XYZ-coordinate system. The slit is located parallel to the Y axis; θ is the angle between the mirror’s normal axis and the optical axis; and hλ is the detector plane that is parallel to the YZ plane.

Fig. 2
Fig. 2

Assembled instrument: M, rotary table; T, front surface mirror; L1, front lens; A, 35-mm camera lens adapter; O, laser pointer; B, 10-cm optic mount barrel; L3, the camera lens; CCD, the camera head; I, the lift table; and E, two steel bars.

Fig. 3
Fig. 3

Results of both wavelength and absolute calibrations. The wavelength calibration was obtained by use of a mercury vapor gas lamp. The green mercury emission line at 5461 Å is marked. C(λ) is the spectrum of the diffuse reemitting screen illuminated by a tungsten absolute calibration lamp. Note that C is the average slit response given in raw counts (cts/s). The exposure time was 200 ms. B 0(λ) represents the spectrum for the 1000-W tungsten lamp in units of mW/m2 Å.

Fig. 4
Fig. 4

First nine images from left to right in ascending order represent the reflective characteristics of a shrimp at the center wavelengths 4432, 4742, 5054, 5365, 5678, 5991, 6304, 6618, and 6933 Å, respectively. We obtained each individual image by summing an incremental wavelength region of 310 Å. The intensity is given in raw counts from the detector with a maximum count of 890/s at a 6304-Å center wavelength. The exposure time was 200 ms. Also shown is a composite color image that we generated by combining three images measured at 6304 Å (red), 5678 Å (green), and 4742 Å (blue). The last two images show the results of the classification, including one corresponding boiled shrimp. The red and pink filled squares represent different shell types. The yellow square indicates those portions of the shrimp that were peeled.

Fig. 5
Fig. 5

First 14 images from left to right in ascending order represent the spectral characteristics of a fish parasite at the center wavelengths 4277, 4483, 4691, 4898, 5105, 5313, 5521, 5730, 5938, 6147, 6356, 6566, 6775, and 6985 Å. We obtained each individual image by summing an incremental wavelength region of 210 Å. The response of the instrument was calibrated. The maximum reflected intensity was 465 mW/m2 at the center wavelength of 6566 Å. The exposure time was 200 ms. Also shown is the composite color image that we generated by combining three images measured at 6356 Å (red), 5521 Å (green), and 4898 Å (blue). The last image shows the results of the classification as follows: red, parasite; green, shadow; blue, needle head; yellow, needle; light blue, fish muscle; white, overcounts; and gray, background. Black represents unclassified pixels.

Fig. 6
Fig. 6

Landscape images taken from the roof of the Auroral Observatory in Tromsø, Norway, 14:00 UT, 7 July 1998. Blåamann is the highest mountain located west of the observatory. The three images in (a), (b), and (c) have center wavelengths of 6323, 5526 and 4819 Å, respectively. We obtained each individual image by summing an incremental wavelength region of 42 Å. The exposure time was 40 ms. Image (d) shows the resulting color image that we obtained by making a composite RGB image from (a), (b), and (c). Panel (e) shows a range of spectra according to the selected pixels in image (a). Red lines connect the selected pixels to the corresponding spectra. In ascending order the spectra represent the reflected and scattered light from the center of a small cloud, scattered light from the blue sky, reflected light from both the peak of Blåmann and the snow cover from the Hollendaren mountain.

Fig. 7
Fig. 7

Landscape images taken from Longyearbyen, Norway, 08:30 UT, 16 September 1998. The marine vessel is the Polarstern. The three images in (a), (b), and (c) have center wavelengths of 6356, 5521, and 4898 Å, respectively. We obtained each individual image by summing an incremental wavelength region of 210 Å. The exposure time was 200 ms. We obtained the resulting color image in (d) by making a composite RGB image from (a), (b), and (c). Image (e) is the result of classification by use of the Bayes method, whereas (f) shows the corresponding result after use of the Minimum distance method. Panel (g) shows a range of spectra according to the selected pixels in image (a). Red lines connect the selected pixels to the corresponding spectra. In ascending order the spectra represent the reflected light from the ship’s bridge and hull, seawater, cloudy sky, river bank, and hut, respectively.

Fig. 8
Fig. 8

Instrumental platform mounted inside the airborne carrier (Dornier 228–202 K): (a) spectral imager, (b) video camera, (c) tripod, (d) dome, (e) warm air pipe.

Fig. 9
Fig. 9

Airborne images from Vestpynten close to the Longyearbyen Airport, Norway, 11:15 UT, 15 April 1999. The three monochromatic images in (a), (b), and (c) have center wavelengths of 5819, 5294, and 4873 Å, respectively. We obtained each individual image by summing an incremental wavelength region of 105 Å. The exposure time was 60 ms. We obtained the false color image in (d) by making a composite RGB image from (a), (b), and (c). Image (e) is the result of classification by use of the Bayes method. Panel (f) shows a range of spectra according to the selected positions in image (a). The colored circles mark the selected positions to the ir corresponding spectra. The spectra represent the reflected light from snow cover onshore (red circle), leads (blue circle), and different types of sea ice (white, green, yellow, and pink circles).

Tables (2)

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Table 1 Instrumental Parameters for the Airborne Campaigna

Tables Icon

Table 2 Description of Airborne Targetsa

Equations (6)

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Iθ=Iθλ, h mW/m2Å,
Jθλc, h=λsλe Iθλ, hdλ mW/m2,
Δθ=2arctanw21f-1p deg,
Δx=2ptanΔθ/2 m.
Δx=Δx+Vτe m,
K=Kλ, h=B0λCθ=ϕ0λ, hrR2 cos ϕ0mWm2Åctss,

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